Design Of Temperature Control System For Kiln Based On Fuzzy Neural Network Control

Lime and limestone are widely used as building materials and are also important raw materials in many industries.In modern industry,lime is not only widely used in construction,but also a necessary material in chemical industry,especially in modern chemical production.It not only has high demand for lime production,but also has higher requirements for lime active quality,etc.How to produce more and higher quality lime is the problem that lime kiln needs to face now.At the same time,for the pharmaceutical industry,the higher requirement now is lower lime overburning.Some manufacturers have explicitly required lime overburning to be less than 3%.The traditional lime production cannot meet the requirements for temperature control and cannot guarantee the final quality of lime.With this problem in front of us,lime production needs to improve its temperature control.Lime kiln is a nonlinear,strongly coupled,multivariable and multi-interference complex control system,which mainly includes three control directions: adjusting combustion air volume to ensure the pressure in the kiln chamber and ensure the safe operation of the system;Ensure that the combustion-supporting air coefficient is kept within the optimal range to achieve higher combustion efficiency and ensure the economy of the system control process;Ensure kiln temperature output is within normal range.However,these requirements can no longer be met by traditional control methods.Combined with modern advanced control methods,fuzzy neural network combines the advantages of fuzzy control and BP neural network.Fuzzy system not only does not need to establish a more accurate mathematical model for the control system,but also uses BP neural network to spread the error between the actual output and the expected output in reverse,so as to correct the membership function and weight value of the system and stabilize the system output in a shorter time.In this paper,the operation characteristics of the system and the difficulties of kiln temperature control are introduced,the present situation and problems of kiln control are analyzed,and the design scheme is put forward.Secondly,the multi-input and multi-output structure of the system is analyzed and decoupled,and the control channel of furnace temperature is controlled by the amount of coal,and the next step is mainly analyzed and controlled.Then the fuzzy PID control mode of the system is constructed through the fuzzy control theory to realize the fuzzy controller design of the system.Then the fuzzy PID control parameters were adjusted by using the reverse propagation algorithm of BP neural network,which combined the neural network with fuzzy control.Finally,the simulation analysis of the design system and the use of communication method to analyze the actual kiln operation status with the fixed data to verify the effective rationality of the design.This paper introduces the characteristics of fuzzy system and BP neural network,as well as the combination points and characteristics of the two control methods.It is applied to the kiln temperature control system,the PID parameters of the system are adjusted by fuzzy neural network control method,and the system under fuzzy neural network control is simulated by MATLAB.Compared with the traditional PID control method,the adjusted parameters are finally applied to the actual kiln operation,and the equipment operation and data acquisition are completed by PLC control.According to the operation effect,the superiority of the system control under this control method is analyzed from various angles.